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Virtual immunohistochemistry staining using deep learning techniques
Wang, Qiang
(Principal Investigator)
Akram, Ahsan
(Principal Investigator)
Hopgood, James
(Principal Investigator)
Deanery of Clinical Sciences
Centre for Inflammation Research
Edinburgh Cancer Research Centre
School of Engineering
Acoustics and Audio Group
Overview
Fingerprint
Research output
(1)
Project Details
Status
Finished
Effective start/end date
1/01/23
→
31/03/24
View all
View less
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Deep Learning Method
Computer Science
100%
Fluorescence Lifetime Imaging Microscopy
Engineering
100%
Label-Free
Physics
100%
Deep Learning Model
Computer Science
50%
Image Quality
Computer Science
50%
Fundamental Importance
Computer Science
50%
Microenvironments
Engineering
12%
Fluorophore
Engineering
12%
Research output
Research output per year
2024
2024
2024
1
Article
Research output per year
Research output per year
Deep learning-based virtual H&E staining from label-free autofluorescence lifetime images
Wang, Q.,
Akram, A. R.
, Dorward, D., Talas, S., Monks, B., Thum, C.,
Hopgood, J. R.
,
Javidi, M.
& Vallejo, M.,
28 Jun 2024
, (E-pub ahead of print)
In:
njp Imaging.
2
,
1
,
p. 17
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
File
Deep Learning Method
100%
Fluorescence Lifetime Imaging Microscopy
100%
Label-Free
100%
Image Quality
50%
Fundamental Importance
50%